The BeAPI Framework is ...

  • Plug-N-Play
  • Asynchronous
  • Distributed

It's a Microservice API Framework that scales as your infrastructure and company grows. It simplifies the entire API development process so that even a startup can have an architecture that can scale all the way to enterprise with very few changes.

The BeAPI Framework automates the entire API process (ie URL mapping, checks, caching, etc) and abstract communication processes away from business logic so that I/O can more effectively be shared with other processes in your architecture. This makes scaling easier and speeds up your entire system..


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API Chaining

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API Multitenancy

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Shared I/O State

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CQRS

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Localized Cache

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Asynchronous Batching

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Fully Automated I/O Checks

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Built-In API Docs

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API Chaining(tm)

API Chaining,one of our greatest inventions, is also perhaps one of the most misunderstood. Described as a 'client side monad' enabling multiple request/responses to be done in a single request/response call, most people mistake this for method chaining (aka 'train wreck') and implement this incorrectly. Proper implementations can get speed increases of up to 85% over traditional calls when doing a 3 chained call.

API chaining has been written about in ProgrammableWeb, NetworkWorld and drawn the attention of multiple enterprises looking to improve their network calls for mobile and IOT. To this day, it is still the number one invention we get the most traction and attention for.

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API Abstraction & The New API Pattern

Of course, none of this could be possible without the concept of API abstraction. The original API pattern was invented in the 1970's when distributed architectures did not exist and the communication (I/O) was bound to business logic in the original API pattern. This was fine for centralized architecture but created an architectural cross cutting concern in distributed architectures.

As a result, the API Pattern had to be rewritten for distributed architectures to abstract communication data/functionality away from business logic. This led to better speed, scalability and new patterns like API Chaining.

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Shared I/O State

By storing I/O data in a common document that can be cached and reloaded on the fly, we manage to separate data from functionality. This better enables us to establish a Standard Version Of Truth(SVOT) from which all other services in the architecture can synchronize from.

This allows all data associated with endpoint access to be synchronized without duplication. And it can be reloaded on the fly without taking any services down.

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